The next NCBO Webinar will be presented by Erich Gombocz from IO Informatics
on "Semantic cross-domain integration: The intersection of research,
public, and clinical data; creating applicable knowledge for decision
support in patient-centric healthcare" at 10:00am PT, Wednesday, May 4.
Below is information on how to join the online meeting via WebEx and
accompanying teleconference. For the full schedule of the NCBO Webinar
presentations see: http://www.bioontology.org/webinar-series.
ABSTRACT:
While cross-domain data integration has been acknowledged to play a key role
in translational research, it has remained challenging in conventional
settings due to time and cost barriers for initial integration and lack of
flexibility and extensibility as resources and needs evolve. This is where
semantic methods excel, not only due to their support for dynamic needs, but
also due to the fact that a network-based data model is more apt to handle
complex biological systems.
Biomarker qualification and validation with functional insights on a systems
scale is demanding. Unifying public resources and internal datasets and
proper weighing of markers is non-trivial. Therefore, the use of biomarkers
from multiple modalities (-OMICs, imaging, clinical endpoints), while
increasing in the scientific community, has, for the most part, lagged
behind the promise for their use in patient screening and decision support.
This is partly because of the difficulties in meaningful semantic
integration of heterogeneous experimental and public data, and the
complexity in understanding the involved biological functions. Both of these
essential challenges need to be addressed to make a resulting knowledgebase
applicable for decision support in clinics.
Building on advanced resource description framework standards (RDF), the
ease of semantic integration methods to overcome these challenges is shown.
Integration of heterogeneous sources, taxonomies, ontologies,
non-standardized vocabularies and the complexity in meaningful integration
of multiple -OMICs data sets with clinical observations will be
demonstrated. In this case, the Sentientâ„¢ Suite will be applied to capture
semantic patterns and create predictive network models, using virtually any
combination of internal experimental data and / or external published
information. These patterns apply semantic SPARQL query technology to
visually build complex searches across multiple information sets.
Based on three recent customer examples, Sentient has applied semantic
standards to provide the framework for:
â€¢ Assessment of treatment effectiveness for combinatorial prostate cancer
therapies;
â€¢ Pre-symptomatic detection, scoring and stratification of transplant
patients at risk of heart or kidney failure; and
â€¢ Impact of inflammatory responses in high risk plaque rupture
Semantic linking of experimental correlation networks with curated public
domain knowledge networks (via direct queries or from SPARQL endpoints,
such as LODD) helps researchers gain a better understanding of mechanistic
aspects of biomarkers at a functional level. In this demonstration,
application ontologies derived from experimental data and analytical results
will be merged with formal public ontologies (such as NCBO, OBO). Resulting
hypotheses can be captured in arrays of rich SPARQL queries representing
biological signatures. This session will conclude with a discussion on how
these profiles can be stored in an Applied Semantic Knowledgebase (ASK) for
further validation or application unique to a specific research focus and
how this knowledge is applied to highly sensitive, specific and scored
patient screening â€“ providing decision support for life sciences and
personalized patient-centric healthcare.
References:
1) R. Stanley, B. McManus, R. Ng, E. Gombocz, J. Eshleman, C. Rockey: Case
Study: Applied Semantic Knowledgebase for Detection of Patients at Risk of
Organ Failure through Immune
Rejection<http://www.w3.org/2001/sw/sweo/public/UseCases/IOInformatics/>,
World Wide Web Consortium (W3C) Semantic Web Use Cases and Case Studies
(2011).
2) E. Gombocz, R. Stanley, J. Eshleman: Computational R&D in Action:
Integrating Correlation and Knowledge Networks For Treatment Response
Modeling and Decision
Support<http://www.io-informatics.com/news/pdfs/POSTER_CompDrugR&D2010_20100920.pdf>
Advanced Strategies for Computational Drug R&D (2010).
SPEAKER BIO:
Dr. Erich Gombocz has more than 30 years of experience in Life Science
research, laboratory automation and data management in scientific and
distributed systems environments, and more than 30 years programming
experience in instrumentation control, user interface, database design,
scientific analysis, and on-line laboratory automation as well as being
developer of innovative software algorithms and architecture.
Focusing on semantic data integration and knowledge management in life
sciences, he founded IO Informatics in 2003 together with Bob Stanley to
apply systems biology approaches to challenges in the area of pharmaceutical
and clinical decision-making.
Dr. Gombocz has published over 60 scientific publications and holds
currently more than 40 biotechnology- and software-related US and
international patents. He is an international expert in separation science
and bioinformatics, a member of several professional organizations, and
serves on the editorial board of a number of scientific journals.
WEBEX DETAILS:
Go to
https://stanford.webex.com/stanford/j.php?ED=107799137&UID=481527042&PW=NNjE3OWYzODk3&RT=MiM0
Call-in toll number (US/Canada): 1-650-429-3300
Global call-in numbers:
https://stanford.webex.com/stanford/globalcallin.php?serviceType=MC&ED=107799137&tollFree=0
Access code:926 719 478